During the first two years of our active CISNET project "Survival Effects of Prostate Cancer Surveillance" a population model of prostate cancer incidence and mortality was developed and applied to analyze national population and cancer registry data. The new application will focus on using the model to understand, predict and optimize the population impact of cancer control processes in prostate cancer. Specifically, we will study the joint effect of progress in treatment of prostate cancer and dissemination of PSA on observed national incidence and mortality trends;make short- and long-term predictions of the trends;analyze racial disparities as they pertain to dissemination of PSA testing, natural history of prostate cancer, benign disorders in the prostate, dissemination of treatment, survival, incidence and mortality;assess the effect of misattribution bias on the patterns of prostate cancer mortality;evaluate the sensitivity of estimates of population impact of screening interventions and treatment on mortality;assess the impact of Transurethral Resection of the Prostate (TURP) on early detection of prostate cancer and population trends in the pre-PSA era;develop unbiased assessment of treatment effects from population data;translate the results of clinical and prevention trials, and retrospective analyses of clinical data in prostate cancer into the potential population impact of their dissemination;determine and evaluate optimal screening strategies and predict their effect on future national trends in prostate cancer incidence and mortality;develop a user-friendly interface for the model.